New Hybrid (SVMs -CSOA) Architecture for classifying Electrocardiograms Signals
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2015, Vol 4, Issue 5
Abstract
a medical test that provides diagnostic relevant information of the heart activity is obtained by means of an ElectroCardioGram (ECG). Many heart diseases can be found by analyzing ECG because this method with moral performance is very helpful for shaping human heart status. Support Vector Machines (SVM) has been widely applied in classification. In this paper we present the SVM parameter optimization approach using novel metaheuristic for evolutionary optimization algorithms is Cat Swarm Optimization Algorithm (CSOA). The results obtained assess the feasibility of new hybrid (SVMs -CSOA) architecture and demonstrate an improvement in terms of accuracy.
Authors and Affiliations
Assist. Prof. Majida Abed, Assist. Prof. Dr. Hamid Alasad
Keywords
Related Articles
- EP ID EP158489
- DOI 10.14569/IJARAI.2015.040505
- Views 132
- Downloads 0
Method for Reducing the Number of Wild Animal Monitors by Means of Kriging
Method for reducing the number of wild animal monitors is proposed by means of Kriging. Through wild animal route of simulations with 128 by 128 cells, the required number of wild animal monitors is clarified. Then...
Method for 3D Object Reconstruction Using Several Portion of 2D Images from the Different Aspects Acquired with Image Scopes Included in the Fiber Retractor
Method for 3D object reconstruction using several portions of 2D images from the different aspects which are acquired with image scopes included in the fiber retractor is proposed. Experimental results show a great possi...
Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm
This paper presents a method to solve electrical network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and energy not supplied function in di...
Classifications of Motor Imagery Tasks in Brain Computer Interface Using Linear Discriminant Analysis
In this paper, we address a method for motor imagery feature extraction for brain computer interface (BCI). The wavelet coefficients were used to extract the features from the motor imagery EEG and the linear discr...
Case-based Reasoning with Input Text Processing to Diagnose Mood [Affective] Disorders
Case-Based Reasoning is one of the methods used in expert systems. Calculation of similarity degree among the cases has always been an important aspect in CBR as the system will attempt to identify cases with the h...